import pandas as pd
import uuid
import json
import tos
import  time
from bytehouse_driver import Client
import  logging
import  numpy as np
# Access key 和 Secret key 可在用户火山引擎账号中查找
ak = "AKLTMmFmMzVmNmY5ZDEyNDNmNWEyZTU2MDM3Y2EzMDJlZTk"
sk = "WVdNeFpXRXdNekV4Tm1ZME5EZGxPRGc0TUdFNE1HWXdNV1ZqTkdNNU9HRQ=="
# your endpoint 和 your region 填写Bucket 所在区域对应的Endpoint。# 以华北2(北京)为例，your endpoint 填写 tos-cn-beijing.volces.com，your region 填写 cn-beijing。
endpoint = "tos-cn-beijing.ivolces.com"
region = "cn-beijing"


def add_to_bytehouse_dict(dict):
    HOST="bytehouse-cn-beijing.volces.com"
    PORT="19000"
    API_KEY="q2p9nLj7tq:TKOCmgrMKp"
    # 配置数据库连接信息
    DATABASE="dwd"
    client = Client.from_url('bytehouse://{}:{}/?user=bytehouse&password={}&database={}&secure=true'.format(HOST, PORT, API_KEY, DATABASE))
    start_time_str=dict['scid_start_time_str']
    hour = start_time_str[11:13]

    client.execute("INSERT INTO dwd.dwd_trigger_sc_ep40_tda4_v4 VALUES", [
        [dict['vehicle_id'], dict['start_time_str'], dict['scid'], dict['path'], dict['level1'], dict['level2'],
         dict['level3'], dict['day'], dict['month'],dict["scid_start_time_str"], dict['icu2_odometer'], dict['idb3_vehiclespd'],
         dict['acu2_longaccsensorvalue'], dict['acu2_lataccsensorvalue'], dict['acu2_vehicledynyawrate'],
         dict['eps1_steeranglespd'],dict['eps1_torsionbartorque'], dict['cs1_gearpositionreqst'], dict['uid'],dict['day']]])
def get_dict_list(dict):
    data_list=[]
    data_list.append(dict['vehicle_id'])
    data_list.append(dict['start_time_str'])
    data_list.append(dict['scid'])
    data_list.append(dict['path'])
    data_list.append(dict['level1'])
    data_list.append(dict['level2'])
    data_list.append(dict['level3'])
    data_list.append(dict['day'])
    data_list.append(dict['month'])
    data_list.append(dict["scid_start_time_str"])
    data_list.append(dict['icu2_odometer'])
    data_list.append(dict['idb3_vehiclespd'])
    data_list.append(dict['acu2_longaccsensorvalue'])
    data_list.append(dict['acu2_lataccsensorvalue'])
    data_list.append(dict['acu2_vehicledynyawrate'])
    data_list.append(dict['eps1_steeranglespd'])
    data_list.append(dict['eps1_torsionbartorque'])
    data_list.append(dict['cs1_gearpositionreqst'])
    data_list.append(dict['uid'])
    data_list.append(dict['day'])
    return data_list
def add_to_bytehouse(dict_list):

    print(dict_list)
    HOST="bytehouse-cn-beijing.volces.com"
    PORT="19000"
    API_KEY="q2p9nLj7tq:TKOCmgrMKp"
    # 配置数据库连接信息
    DATABASE="dwd"
    client = Client.from_url('bytehouse://{}:{}/?user=bytehouse&password={}&database={}&secure=true'.format(HOST, PORT, API_KEY, DATABASE))
    client.execute("INSERT INTO dwd.dwd_trigger_sc_ep40_tda4_v4 VALUES", dict_list)
def get_scid_time(df_expected_takeover_ads_100ms):
    df_expected_takeover_ads_100ms_list = df_expected_takeover_ads_100ms[
        ['start_time_str', 'path', 'nsecs', 'VLCCDHypotheses_Hypothesis_0_fTTC', 'VLCCDHypotheses_Hypothesis_0_fDistX',
         'VLCCDHypotheses_Hypothesis_0_fDistY',
         'VLCCDHypotheses_Hypothesis_0_fVrelX', 'VLCCDHypotheses_Hypothesis_0_fVrelY', 'IDB3_VehicleSpd',
         'ACU2_LongAccSensorValue', 'ACU2_LatAccSensorValue',
         'ACU2_VehicleDynYawRate', 'IDB1_BrakePedalApplied', 'EPS1_SteerAngleSpd',
         'CamLaneData_CourseInfo_1_CourseInfoSegNear_f_C0',
         'ADCS8_longitudCtrlTakeOverReq', 'ADCS8_lateralCtrtakeove','ICU2_Odometer','EPS1_TorsionBarTorque','CS1_GearPositionReqSt'
         ]].values.tolist()


    found_index = -9999
    start_time_str = ""
    found_ICU2_Odometer=0.0
    found_IDB3_VehicleSpd=0.0
    found_ACU2_LongAccSensorValue=0.0
    found_ACU2_LatAccSensorValue=0.0
    found_ACU2_VehicleDynYawRate=0.0
    found_EPS1_SteerAngleSpd=0.0
    found_EPS1_TorsionBarTorque=0.0
    found_CS1_GearPositionReqSt=0
    # 遍历列表

    for index, element in enumerate(df_expected_takeover_ads_100ms_list):
        start_time_str = element[0]
        path = element[1]
        nsecs = element[2]
        ADCS8_longitudCtrlTakeOverReq = element[15]
        ADCS8_lateralCtrtakeove = element[16]

        ICU2_Odometer = element[17]
        IDB3_VehicleSpd = element[8]
        ACU2_LongAccSensorValue = element[9]
        ACU2_LatAccSensorValue = element[10]
        ACU2_VehicleDynYawRate = element[11]
        EPS1_SteerAngleSpd = element[13]
        EPS1_TorsionBarTorque = element[18]
        CS1_GearPositionReqSt = element[19]
        if (ADCS8_longitudCtrlTakeOverReq==1) or (ADCS8_lateralCtrtakeove==1):
            found_index = index
            found_ICU2_Odometer = ICU2_Odometer
            found_IDB3_VehicleSpd = IDB3_VehicleSpd
            found_ACU2_LongAccSensorValue = ACU2_LongAccSensorValue
            found_ACU2_LatAccSensorValue = ACU2_LatAccSensorValue
            found_ACU2_VehicleDynYawRate = ACU2_VehicleDynYawRate
            found_EPS1_SteerAngleSpd = EPS1_SteerAngleSpd
            found_EPS1_TorsionBarTorque = EPS1_TorsionBarTorque
            found_CS1_GearPositionReqSt = CS1_GearPositionReqSt

            break  # 找到第一个符合条件的元素就跳出循环
    logging.info("found_index: " + str(found_index))
    dict_scid={}
    dict_scid["scid_start_time_str"]=start_time_str
    dict_scid["ICU2_Odometer"] = found_ICU2_Odometer
    dict_scid["IDB3_VehicleSpd"] = found_IDB3_VehicleSpd
    dict_scid["ACU2_LongAccSensorValue"] = found_ACU2_LongAccSensorValue
    dict_scid["ACU2_LatAccSensorValue"] = found_ACU2_LatAccSensorValue
    dict_scid["ACU2_VehicleDynYawRate"] = found_ACU2_VehicleDynYawRate
    dict_scid["EPS1_SteerAngleSpd"] = found_EPS1_SteerAngleSpd
    dict_scid["EPS1_TorsionBarTorque"] = found_EPS1_TorsionBarTorque
    dict_scid["CS1_GearPositionReqSt"] = found_CS1_GearPositionReqSt
    return dict_scid
def get_model_feature(found_index,df_list,start_time_str):
    if found_index >= 11:
        VLCCDHypotheses_Hypothesis_0_fTTC_last_list = df_list[found_index - 11:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fTTC_last= [row[3] for row in VLCCDHypotheses_Hypothesis_0_fTTC_last_list]
        VLCCDHypotheses_Hypothesis_0_fTTC_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fTTC_last)
        AEB_Target_Estimated_Time_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fTTC_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fTTC_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fTTC_next =[row[3] for row in VLCCDHypotheses_Hypothesis_0_fTTC_next_list]
        VLCCDHypotheses_Hypothesis_0_fTTC_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fTTC_next)
        AEB_Target_Estimated_Time_post = np.mean(VLCCDHypotheses_Hypothesis_0_fTTC_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistX_last_list = df_list[found_index - 11:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fDistX_last= [row[4] for row in VLCCDHypotheses_Hypothesis_0_fDistX_last_list]
        VLCCDHypotheses_Hypothesis_0_fDistX_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistX_last)
        AEB_Target_Longitudinal_Distance_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fDistX_last_nnp)


        VLCCDHypotheses_Hypothesis_0_fDistX_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fDistX_next= [row[4] for row in VLCCDHypotheses_Hypothesis_0_fDistX_next_list]
        VLCCDHypotheses_Hypothesis_0_fDistX_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistX_next)
        AEB_Target_Longitudinal_Distance_post = np.mean(VLCCDHypotheses_Hypothesis_0_fDistX_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistY_last_list = df_list[found_index - 11:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fDistY_last = [row[5] for row in VLCCDHypotheses_Hypothesis_0_fDistY_last_list]
        VLCCDHypotheses_Hypothesis_0_fDistY_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistY_last)
        AEB_Target_Cross_Range_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fDistY_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistY_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fDistY_next = [row[5] for row in VLCCDHypotheses_Hypothesis_0_fDistY_next_list]
        VLCCDHypotheses_Hypothesis_0_fDistY_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistY_next)
        AEB_Target_Cross_Range_post = np.mean(VLCCDHypotheses_Hypothesis_0_fDistY_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelX_last_list = df_list[found_index - 11:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fVrelX_last = [row[6] for row in VLCCDHypotheses_Hypothesis_0_fVrelX_last_list]
        VLCCDHypotheses_Hypothesis_0_fVrelX_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelX_last)
        AEB_Target_Longitudinal_Velocity_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelX_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelX_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fVrelX_next = [row[6] for row in VLCCDHypotheses_Hypothesis_0_fVrelX_next_list]
        VLCCDHypotheses_Hypothesis_0_fVrelX_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelX_next)
        AEB_Target_Longitudinal_Velocity_post = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelX_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelY_last_list = df_list[found_index - 11:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fVrelY_last = [row[7] for row in VLCCDHypotheses_Hypothesis_0_fVrelY_last_list]
        VLCCDHypotheses_Hypothesis_0_fVrelY_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelY_last)
        AEB_Target_Lateral_Velocity_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelY_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelY_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fVrelY_next = [row[7] for row in VLCCDHypotheses_Hypothesis_0_fVrelY_next_list]
        VLCCDHypotheses_Hypothesis_0_fVrelY_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelY_next)
        AEB_Target_Lateral_Velocity_post = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelY_next_nnp)

        IDB3_VehicleSpd_last_list = df_list[found_index - 11:found_index - 1]
        IDB3_VehicleSpd_last = [row[8] for row in IDB3_VehicleSpd_last_list]
        IDB3_VehicleSpd_last_nnp = np.array(IDB3_VehicleSpd_last)
        IDB3_VehicleSpd_pre = np.mean(IDB3_VehicleSpd_last_nnp)

        IDB3_VehicleSpd_last_next_list = df_list[found_index + 1:found_index + 11]
        IDB3_VehicleSpd_last_next = [row[8] for row in IDB3_VehicleSpd_last_next_list]
        IDB3_VehicleSpd_last_next_nnp = np.array(IDB3_VehicleSpd_last_next)
        IDB3_VehicleSpd_post = np.mean(IDB3_VehicleSpd_last_next_nnp)

        ACU2_LongAccSensorValue_last_list = df_list[found_index - 11:found_index - 1]
        ACU2_LongAccSensorValue_last = [row[9] for row in ACU2_LongAccSensorValue_last_list]
        ACU2_LongAccSensorValue_last_nnp = np.array(ACU2_LongAccSensorValue_last)
        ACU2_LongAccSensorValue_pre = np.mean(ACU2_LongAccSensorValue_last_nnp)

        ACU2_LongAccSensorValue_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_LongAccSensorValue_next = [row[9] for row in ACU2_LongAccSensorValue_next_list]
        ACU2_LongAccSensorValue_next_nnp = np.array(ACU2_LongAccSensorValue_next)
        ACU2_LongAccSensorValue_post = np.mean(ACU2_LongAccSensorValue_next_nnp)

        ACU2_LatAccSensorValue_last_list = df_list[found_index - 11:found_index - 1]
        ACU2_LatAccSensorValue_last = [row[10] for row in ACU2_LatAccSensorValue_last_list]
        ACU2_LatAccSensorValue_last_nnp = np.array(ACU2_LatAccSensorValue_last)
        ACU2_LatAccSensorValue_pre = np.mean(ACU2_LatAccSensorValue_last_nnp)

        ACU2_LatAccSensorValue_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_LatAccSensorValue_next = [row[10] for row in ACU2_LatAccSensorValue_next_list]
        ACU2_LatAccSensorValue_next_nnp = np.array(ACU2_LatAccSensorValue_next)
        ACU2_LatAccSensorValue_post = np.mean(ACU2_LatAccSensorValue_next_nnp)

        ACU2_VehicleDynYawRate_last_list = df_list[found_index - 11:found_index - 1]
        ACU2_VehicleDynYawRate_last = [row[11] for row in ACU2_VehicleDynYawRate_last_list]
        ACU2_VehicleDynYawRate_last_nnp = np.array(ACU2_VehicleDynYawRate_last)
        ACU2_VehicleDynYawRate_pre = np.mean(ACU2_VehicleDynYawRate_last_nnp)

        ACU2_VehicleDynYawRate_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_VehicleDynYawRate_next = [row[11] for row in ACU2_VehicleDynYawRate_next_list]
        ACU2_VehicleDynYawRate_next_nnp = np.array(ACU2_VehicleDynYawRate_next)
        ACU2_VehicleDynYawRate_post = np.mean(ACU2_VehicleDynYawRate_next_nnp)

        AEB_Target_Estimated_Time_diff = AEB_Target_Estimated_Time_post - AEB_Target_Estimated_Time_pre
        AEB_Target_Longitudinal_Distance_diff = AEB_Target_Longitudinal_Distance_post - AEB_Target_Longitudinal_Distance_pre
        AEB_Target_Cross_Range_diff = AEB_Target_Cross_Range_post - AEB_Target_Cross_Range_pre
        AEB_Target_Longitudinal_Velocity_diff = AEB_Target_Longitudinal_Velocity_post - AEB_Target_Longitudinal_Velocity_pre
        AEB_Target_Lateral_Velocity_diff = AEB_Target_Lateral_Velocity_post - AEB_Target_Lateral_Velocity_pre
        IDB3_VehicleSpd_diff = IDB3_VehicleSpd_post - IDB3_VehicleSpd_pre
        ACU2_LongAccSensorValue_diff = ACU2_LongAccSensorValue_post - ACU2_LongAccSensorValue_pre
        ACU2_LatAccSensorValue_diff = ACU2_LatAccSensorValue_post - ACU2_LatAccSensorValue_pre
        ACU2_VehicleDynYawRate_diff = ACU2_VehicleDynYawRate_post - ACU2_VehicleDynYawRate_pre

        IDB1_BrakePedalApplied_next_list = df_list[found_index + 1:found_index + 11]
        IDB1_BrakePedalApplied_next = [row[12] for row in IDB1_BrakePedalApplied_next_list]
        IDB1_BrakePedalApplied_next_nnp = np.array(IDB1_BrakePedalApplied_next)
        IDB1_BrakePedalApplied = np.mean(IDB1_BrakePedalApplied_next_nnp)

        EPS1_SteerAngleSpd_next_list = df_list[found_index + 1:found_index + 11]
        EPS1_SteerAngleSpd_next = [row[13] for row in EPS1_SteerAngleSpd_next_list]
        EPS1_SteerAngleSpd_next_nnp = np.array(EPS1_SteerAngleSpd_next)
        EPS1_SteerAngleSpd = np.max(EPS1_SteerAngleSpd_next_nnp)

        if found_index - 31 >= 0:
            lane_curve_list_fat = df_list[found_index - 31:found_index - 1]
            lane_curve_list = [row[14] for row in lane_curve_list_fat]
        else:
            lane_curve_list_fat = df_list[0:found_index - 1]
            lane_curve_list = [row[14] for row in lane_curve_list_fat]
        lane_curve = max(map(abs, lane_curve_list))
        logging.info("lane_curve: "+str(lane_curve))

        hour = start_time_str[11:13]
        data = {'AEB_Target_Estimated_Time_pre': [AEB_Target_Estimated_Time_pre],
                'AEB_Target_Estimated_Time_post': [AEB_Target_Estimated_Time_post],
                'AEB_Target_Longitudinal_Distance_pre': [AEB_Target_Longitudinal_Distance_pre],
                'AEB_Target_Longitudinal_Distance_post': [AEB_Target_Longitudinal_Distance_post],
                'AEB_Target_Cross_Range_pre': [AEB_Target_Cross_Range_pre],
                'AEB_Target_Cross_Range_post': [AEB_Target_Cross_Range_post],
                'AEB_Target_Longitudinal_Velocity_pre': [AEB_Target_Longitudinal_Velocity_pre],
                'AEB_Target_Longitudinal_Velocity_post': [AEB_Target_Longitudinal_Velocity_post],
                'AEB_Target_Lateral_Velocity_pre': [AEB_Target_Lateral_Velocity_pre],
                'AEB_Target_Lateral_Velocity_post': [AEB_Target_Lateral_Velocity_post],
                'IDB3_VehicleSpd_pre': [IDB3_VehicleSpd_pre],
                'IDB3_VehicleSpd_post': [IDB3_VehicleSpd_post],
                'ACU2_LongAccSensorValue_pre': [ACU2_LongAccSensorValue_pre],
                'ACU2_LongAccSensorValue_post': [ACU2_LongAccSensorValue_post],
                'ACU2_LatAccSensorValue_pre': [ACU2_LatAccSensorValue_pre],
                'ACU2_LatAccSensorValue_post': [ACU2_LatAccSensorValue_post],
                'ACU2_VehicleDynYawRate_pre': [ACU2_VehicleDynYawRate_pre],
                'ACU2_VehicleDynYawRate_post': [ACU2_VehicleDynYawRate_post],
                'AEB_Target_Estimated_Time_diff': [AEB_Target_Estimated_Time_diff],
                'AEB_Target_Longitudinal_Distance_diff': [AEB_Target_Longitudinal_Distance_diff],
                'AEB_Target_Cross_Range_diff': [AEB_Target_Cross_Range_diff],
                'AEB_Target_Longitudinal_Velocity_diff': [AEB_Target_Longitudinal_Velocity_diff],
                'AEB_Target_Lateral_Velocity_diff': [AEB_Target_Lateral_Velocity_diff],
                'IDB3_VehicleSpd_diff': [IDB3_VehicleSpd_diff],
                'ACU2_LongAccSensorValue_diff': [ACU2_LongAccSensorValue_diff],
                'ACU2_LatAccSensorValue_diff': [ACU2_LatAccSensorValue_diff],
                'ACU2_VehicleDynYawRate_diff': [ACU2_VehicleDynYawRate_diff],
                'IDB1_BrakePedalApplied': [IDB1_BrakePedalApplied],
                'EPS1_SteerAngleSpd': [EPS1_SteerAngleSpd],
                'lane_curve': [lane_curve],
                'hour': [hour]
                }
        df = pd.DataFrame(data)
        print(df)

    else:
        VLCCDHypotheses_Hypothesis_0_fTTC_last_list = df_list[0:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fTTC_last= [row[3] for row in VLCCDHypotheses_Hypothesis_0_fTTC_last_list]
        VLCCDHypotheses_Hypothesis_0_fTTC_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fTTC_last)
        AEB_Target_Estimated_Time_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fTTC_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fTTC_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fTTC_next =[row[3] for row in VLCCDHypotheses_Hypothesis_0_fTTC_next_list]
        VLCCDHypotheses_Hypothesis_0_fTTC_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fTTC_next)
        AEB_Target_Estimated_Time_post = np.mean(VLCCDHypotheses_Hypothesis_0_fTTC_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistX_last_list = df_list[0:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fDistX_last= [row[4] for row in VLCCDHypotheses_Hypothesis_0_fDistX_last_list]
        VLCCDHypotheses_Hypothesis_0_fDistX_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistX_last)
        AEB_Target_Longitudinal_Distance_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fDistX_last_nnp)


        VLCCDHypotheses_Hypothesis_0_fDistX_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fDistX_next= [row[4] for row in VLCCDHypotheses_Hypothesis_0_fDistX_next_list]
        VLCCDHypotheses_Hypothesis_0_fDistX_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistX_next)
        AEB_Target_Longitudinal_Distance_post = np.mean(VLCCDHypotheses_Hypothesis_0_fDistX_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistY_last_list = df_list[0:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fDistY_last = [row[5] for row in VLCCDHypotheses_Hypothesis_0_fDistY_last_list]
        VLCCDHypotheses_Hypothesis_0_fDistY_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistY_last)
        AEB_Target_Cross_Range_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fDistY_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistY_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fDistY_next = [row[5] for row in VLCCDHypotheses_Hypothesis_0_fDistY_next_list]
        VLCCDHypotheses_Hypothesis_0_fDistY_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistY_next)
        AEB_Target_Cross_Range_post = np.mean(VLCCDHypotheses_Hypothesis_0_fDistY_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelX_last_list = df_list[0:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fVrelX_last = [row[6] for row in VLCCDHypotheses_Hypothesis_0_fVrelX_last_list]
        VLCCDHypotheses_Hypothesis_0_fVrelX_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelX_last)
        AEB_Target_Longitudinal_Velocity_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelX_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelX_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fVrelX_next = [row[6] for row in VLCCDHypotheses_Hypothesis_0_fVrelX_next_list]
        VLCCDHypotheses_Hypothesis_0_fVrelX_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelX_next)
        AEB_Target_Longitudinal_Velocity_post = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelX_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelY_last_list = df_list[0:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fVrelY_last = [row[7] for row in VLCCDHypotheses_Hypothesis_0_fVrelY_last_list]
        VLCCDHypotheses_Hypothesis_0_fVrelY_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelY_last)
        AEB_Target_Lateral_Velocity_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelY_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelY_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fVrelY_next = [row[7] for row in VLCCDHypotheses_Hypothesis_0_fVrelY_next_list]
        VLCCDHypotheses_Hypothesis_0_fVrelY_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelY_next)
        AEB_Target_Lateral_Velocity_post = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelY_next_nnp)

        IDB3_VehicleSpd_last_list = df_list[0:found_index - 1]
        IDB3_VehicleSpd_last = [row[8] for row in IDB3_VehicleSpd_last_list]
        IDB3_VehicleSpd_last_nnp = np.array(IDB3_VehicleSpd_last)
        IDB3_VehicleSpd_pre = np.mean(IDB3_VehicleSpd_last_nnp)

        IDB3_VehicleSpd_last_next_list = df_list[found_index + 1:found_index + 11]
        IDB3_VehicleSpd_last_next = [row[8] for row in IDB3_VehicleSpd_last_next_list]
        IDB3_VehicleSpd_last_next_nnp = np.array(IDB3_VehicleSpd_last_next)
        IDB3_VehicleSpd_post = np.mean(IDB3_VehicleSpd_last_next_nnp)

        ACU2_LongAccSensorValue_last_list = df_list[0:found_index - 1]
        ACU2_LongAccSensorValue_last = [row[9] for row in ACU2_LongAccSensorValue_last_list]
        ACU2_LongAccSensorValue_last_nnp = np.array(ACU2_LongAccSensorValue_last)
        ACU2_LongAccSensorValue_pre = np.mean(ACU2_LongAccSensorValue_last_nnp)

        ACU2_LongAccSensorValue_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_LongAccSensorValue_next = [row[9] for row in ACU2_LongAccSensorValue_next_list]
        ACU2_LongAccSensorValue_next_nnp = np.array(ACU2_LongAccSensorValue_next)
        ACU2_LongAccSensorValue_post = np.mean(ACU2_LongAccSensorValue_next_nnp)

        ACU2_LatAccSensorValue_last_list = df_list[0:found_index - 1]
        ACU2_LatAccSensorValue_last = [row[10] for row in ACU2_LatAccSensorValue_last_list]
        ACU2_LatAccSensorValue_last_nnp = np.array(ACU2_LatAccSensorValue_last)
        ACU2_LatAccSensorValue_pre = np.mean(ACU2_LatAccSensorValue_last_nnp)

        ACU2_LatAccSensorValue_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_LatAccSensorValue_next = [row[10] for row in ACU2_LatAccSensorValue_next_list]
        ACU2_LatAccSensorValue_next_nnp = np.array(ACU2_LatAccSensorValue_next)
        ACU2_LatAccSensorValue_post = np.mean(ACU2_LatAccSensorValue_next_nnp)

        ACU2_VehicleDynYawRate_last_list = df_list[0:found_index - 1]
        ACU2_VehicleDynYawRate_last = [row[11] for row in ACU2_VehicleDynYawRate_last_list]
        ACU2_VehicleDynYawRate_last_nnp = np.array(ACU2_VehicleDynYawRate_last)
        ACU2_VehicleDynYawRate_pre = np.mean(ACU2_VehicleDynYawRate_last_nnp)

        ACU2_VehicleDynYawRate_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_VehicleDynYawRate_next = [row[11] for row in ACU2_VehicleDynYawRate_next_list]
        ACU2_VehicleDynYawRate_next_nnp = np.array(ACU2_VehicleDynYawRate_next)
        ACU2_VehicleDynYawRate_post = np.mean(ACU2_VehicleDynYawRate_next_nnp)

        AEB_Target_Estimated_Time_diff = AEB_Target_Estimated_Time_post - AEB_Target_Estimated_Time_pre
        AEB_Target_Longitudinal_Distance_diff = AEB_Target_Longitudinal_Distance_post - AEB_Target_Longitudinal_Distance_pre
        AEB_Target_Cross_Range_diff = AEB_Target_Cross_Range_post - AEB_Target_Cross_Range_pre
        AEB_Target_Longitudinal_Velocity_diff = AEB_Target_Longitudinal_Velocity_post - AEB_Target_Longitudinal_Velocity_pre
        AEB_Target_Lateral_Velocity_diff = AEB_Target_Lateral_Velocity_post - AEB_Target_Lateral_Velocity_pre
        IDB3_VehicleSpd_diff = IDB3_VehicleSpd_post - IDB3_VehicleSpd_pre
        ACU2_LongAccSensorValue_diff = ACU2_LongAccSensorValue_post - ACU2_LongAccSensorValue_pre
        ACU2_LatAccSensorValue_diff = ACU2_LatAccSensorValue_post - ACU2_LatAccSensorValue_pre
        ACU2_VehicleDynYawRate_diff = ACU2_VehicleDynYawRate_post - ACU2_VehicleDynYawRate_pre

        IDB1_BrakePedalApplied_next_list = df_list[found_index + 1:found_index + 11]
        IDB1_BrakePedalApplied_next = [row[12] for row in IDB1_BrakePedalApplied_next_list]
        IDB1_BrakePedalApplied_next_nnp = np.array(IDB1_BrakePedalApplied_next)
        IDB1_BrakePedalApplied = np.mean(IDB1_BrakePedalApplied_next_nnp)

        EPS1_SteerAngleSpd_next_list = df_list[found_index + 1:found_index + 11]
        EPS1_SteerAngleSpd_next = [row[13] for row in EPS1_SteerAngleSpd_next_list]
        EPS1_SteerAngleSpd_next_nnp = np.array(EPS1_SteerAngleSpd_next)
        EPS1_SteerAngleSpd = np.max(EPS1_SteerAngleSpd_next_nnp)

        lane_curve_list = []
        if found_index - 31 >= 0:
            lane_curve_list_fat = df_list[found_index - 31:found_index - 1]
            lane_curve_list = [row[14] for row in lane_curve_list_fat]
        else:
            lane_curve_list_fat = df_list[0:found_index - 1]
            lane_curve_list = [row[14] for row in lane_curve_list_fat]
        lane_curve = max(map(abs, lane_curve_list))
        logging.info("lane_curve: "+str(lane_curve))

        hour = start_time_str[11:13]
        data = {'AEB_Target_Estimated_Time_pre': [AEB_Target_Estimated_Time_pre],
                'AEB_Target_Estimated_Time_post': [AEB_Target_Estimated_Time_post],
                'AEB_Target_Longitudinal_Distance_pre': [AEB_Target_Longitudinal_Distance_pre],
                'AEB_Target_Longitudinal_Distance_post': [AEB_Target_Longitudinal_Distance_post],
                'AEB_Target_Cross_Range_pre': [AEB_Target_Cross_Range_pre],
                'AEB_Target_Cross_Range_post': [AEB_Target_Cross_Range_post],
                'AEB_Target_Longitudinal_Velocity_pre': [AEB_Target_Longitudinal_Velocity_pre],
                'AEB_Target_Longitudinal_Velocity_post': [AEB_Target_Longitudinal_Velocity_post],
                'AEB_Target_Lateral_Velocity_pre': [AEB_Target_Lateral_Velocity_pre],
                'AEB_Target_Lateral_Velocity_post': [AEB_Target_Lateral_Velocity_post],
                'IDB3_VehicleSpd_pre': [IDB3_VehicleSpd_pre],
                'IDB3_VehicleSpd_post': [IDB3_VehicleSpd_post],
                'ACU2_LongAccSensorValue_pre': [ACU2_LongAccSensorValue_pre],
                'ACU2_LongAccSensorValue_post': [ACU2_LongAccSensorValue_post],
                'ACU2_LatAccSensorValue_pre': [ACU2_LatAccSensorValue_pre],
                'ACU2_LatAccSensorValue_post': [ACU2_LatAccSensorValue_post],
                'ACU2_VehicleDynYawRate_pre': [ACU2_VehicleDynYawRate_pre],
                'ACU2_VehicleDynYawRate_post': [ACU2_VehicleDynYawRate_post],
                'AEB_Target_Estimated_Time_diff': [AEB_Target_Estimated_Time_diff],
                'AEB_Target_Longitudinal_Distance_diff': [AEB_Target_Longitudinal_Distance_diff],
                'AEB_Target_Cross_Range_diff': [AEB_Target_Cross_Range_diff],
                'AEB_Target_Longitudinal_Velocity_diff': [AEB_Target_Longitudinal_Velocity_diff],
                'AEB_Target_Lateral_Velocity_diff': [AEB_Target_Lateral_Velocity_diff],
                'IDB3_VehicleSpd_diff': [IDB3_VehicleSpd_diff],
                'ACU2_LongAccSensorValue_diff': [ACU2_LongAccSensorValue_diff],
                'ACU2_LatAccSensorValue_diff': [ACU2_LatAccSensorValue_diff],
                'ACU2_VehicleDynYawRate_diff': [ACU2_VehicleDynYawRate_diff],
                'IDB1_BrakePedalApplied': [IDB1_BrakePedalApplied],
                'EPS1_SteerAngleSpd': [EPS1_SteerAngleSpd],
                'lane_curve': [lane_curve],
                'hour': [hour]
                }
        df = pd.DataFrame(data)
    return df
def get_can_20ms_list(df_can_20ms_adas_list,nsecs):
    # 找到最接近目标值的行数据
    closest_data = min(df_can_20ms_adas_list, key=lambda x: abs(x[2] - nsecs))

    # 打印结果
    return  closest_data
def uploadjson(bucket_name,object_key,jsonstr):
    try:
        client = tos.TosClientV2(ak, sk, endpoint, region)
        # 若在上传对象时设置文件存储类型（x-tos-storage-class）和访问权限 (x-tos-acl), 请在 put_object中设置相关参数
        # 用户在上传对象时，可以自定义元数据，以便对对象进行自定义管理
        # result = client.put_object(bucket_name, object_key, content=content, acl=tos.ACLType.ACL_Private, storage_class=tos.StorageClassType.Storage_Class_Standard, meta={'name': '张三', 'age': '20'})
        result = client.put_object(bucket_name, object_key, content=jsonstr)
        # HTTP状态码
        print('http status code:{}'.format(result.status_code))
        # 请求ID。请求ID是本次请求的唯一标识，建议在日志中添加此参数
        print('request_id: {}'.format(result.request_id))
        # hash_crc64_ecma 表示该对象的64位CRC值, 可用于验证上传对象的完整性
        print('crc64: {}'.format(result.hash_crc64_ecma))
    except tos.exceptions.TosClientError as e:
        # 操作失败，捕获客户端异常，一般情况为非法请求参数或网络异常
        print('fail with client error, message:{}, cause: {}'.format(e.message, e.cause))
    except tos.exceptions.TosServerError as e:
        # 操作失败，捕获服务端异常，可从返回信息中获取详细错误信息
        print('fail with server error, code: {}'.format(e.code))
        # request id 可定位具体问题，强烈建议日志中保存
        print('error with request id: {}'.format(e.request_id))
        print('error with message: {}'.format(e.message))
        print('error with http code: {}'.format(e.status_code))
        print('error with ec: {}'.format(e.ec))
        print('error with request url: {}'.format(e.request_url))
    except Exception as e:
        print('fail with unknown error: {}'.format(e))
def get_timestamp(time_string):
    # 转换为时间元组
    time_tuple = time.strptime(time_string, "%Y-%m-%d %H:%M:%S")
    # 转换为时间戳
    timestamp = str(int(time.mktime(time_tuple)*1000))
    return timestamp
def get_expected_takeover_ads_label_can_100ms(df_can_100ms_save_path,df_can_20ms_save_path, vechicle_id, daystr, hourstr, bagid, uuids, file_type):
    try:
        df_can_100ms_ads = pd.read_pickle(df_can_100ms_save_path)
    except Exception as e:
        print('data report read error, ', str(e))
    df_can_100ms_ads_list = df_can_100ms_ads[
            ['start_time_str', 'path', 'ADCS8_lateralCtrtakeove', 'EPS1_TorsionBarTorque',
             'ADCS8_longitudCtrlTakeOverReq', 'nsecs', 'IDB3_VehicleSpd', 'AccDisplayObj_CONTROL_ACCEL',
             'ICU2_Odometer', 'ACU2_LongAccSensorValue', 'ACU2_LatAccSensorValue', 'ACU2_VehicleDynYawRate',
             'EPS1_SteerAngleSpd', 'CS1_GearPositionReqSt'
             ]].values.tolist()

    try:
        df_can_20ms_ads = pd.read_pickle(df_can_20ms_save_path)
    except Exception as e:
        print('data report read error, ', str(e))
    df_can_20ms_ads_list = df_can_20ms_ads[
        ['start_time_str', 'path', 'VLCAccOOIData_AccOOINextLong_Attributes_uiObjectID',
         'EnvmGenObjectList_aObject_0_Kinematic_fAabsX','EnvmGenObjectList_aObject_0_Kinematic_fAabsY','EnvmGenObjectList_aObject_0_Kinematic_fDistX','EnvmGenObjectList_aObject_0_Kinematic_fDistY','EnvmGenObjectList_aObject_0_Kinematic_fVabsX','EnvmGenObjectList_aObject_0_Kinematic_fVabsY',
         'EnvmGenObjectList_aObject_1_Kinematic_fAabsX','EnvmGenObjectList_aObject_1_Kinematic_fAabsY','EnvmGenObjectList_aObject_1_Kinematic_fDistX','EnvmGenObjectList_aObject_1_Kinematic_fDistY','EnvmGenObjectList_aObject_1_Kinematic_fVabsX','EnvmGenObjectList_aObject_1_Kinematic_fVabsY',
         'EnvmGenObjectList_aObject_2_Kinematic_fAabsX','EnvmGenObjectList_aObject_2_Kinematic_fAabsY','EnvmGenObjectList_aObject_2_Kinematic_fDistX','EnvmGenObjectList_aObject_2_Kinematic_fDistY','EnvmGenObjectList_aObject_2_Kinematic_fVabsX','EnvmGenObjectList_aObject_2_Kinematic_fVabsY',
         'EnvmGenObjectList_aObject_3_Kinematic_fAabsX','EnvmGenObjectList_aObject_3_Kinematic_fAabsY','EnvmGenObjectList_aObject_3_Kinematic_fDistX','EnvmGenObjectList_aObject_3_Kinematic_fDistY','EnvmGenObjectList_aObject_3_Kinematic_fVabsX','EnvmGenObjectList_aObject_3_Kinematic_fVabsY',
         'EnvmGenObjectList_aObject_4_Kinematic_fAabsX','EnvmGenObjectList_aObject_4_Kinematic_fAabsY','EnvmGenObjectList_aObject_4_Kinematic_fDistX','EnvmGenObjectList_aObject_4_Kinematic_fDistY','EnvmGenObjectList_aObject_4_Kinematic_fVabsX','EnvmGenObjectList_aObject_4_Kinematic_fVabsY',
         'EnvmGenObjectList_aObject_5_Kinematic_fAabsX','EnvmGenObjectList_aObject_5_Kinematic_fAabsY','EnvmGenObjectList_aObject_5_Kinematic_fDistX','EnvmGenObjectList_aObject_5_Kinematic_fDistY','EnvmGenObjectList_aObject_5_Kinematic_fVabsX','EnvmGenObjectList_aObject_5_Kinematic_fVabsY'
         ]].values.tolist()

    #获取触发状态：
    dict_list=[]
    scid_dict=get_scid_time(df_can_100ms_ads)
    found_index = -9999
    # 遍历列表
    ADCS8_lateralCtrtakeove_last=df_can_100ms_ads_list[0][2]
    ADCS8_longitudCtrlTakeOverReq_last=df_can_100ms_ads_list[0][4]
    for index, element in enumerate(df_can_100ms_ads_list):
        start_time_str=element[0]
        path=element[1]
        ADCS8_lateralCtrtakeove=element[2]
        ADCS8_longitudCtrlTakeOverReq=element[4]
        nsecs=element[5]
        AccDisplayObj_CONTROL_ACCEL=element[7]

        ICU2_Odometer = element[8]
        IDB3_VehicleSpd = element[6]
        ACU2_LongAccSensorValue = element[9]
        ACU2_LatAccSensorValue = element[10]
        ACU2_VehicleDynYawRate = element[11]
        EPS1_SteerAngleSpd = element[12]
        EPS1_TorsionBarTorque = element[3]
        CS1_GearPositionReqSt = element[13]


        if index>3:
            if ADCS8_lateralCtrtakeove_last != 1 and ADCS8_lateralCtrtakeove == 1 and index > 3:
                EPS1_TorsionBarTorque_last1 = df_can_100ms_ads_list[index - 1][3]
                EPS1_TorsionBarTorque_last2 = df_can_100ms_ads_list[index - 2][3]
                EPS1_TorsionBarTorque_last3 = df_can_100ms_ads_list[index - 3][3]
                if EPS1_TorsionBarTorque_last1<0.225 and EPS1_TorsionBarTorque_last2<0.225  and EPS1_TorsionBarTorque_last3<0.225:
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "横向接管请求"
                    level3 = "扭矩触发"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)

        if ADCS8_longitudCtrlTakeOverReq_last!=1 and ADCS8_longitudCtrlTakeOverReq==1:
            list_data=get_can_20ms_list(df_can_20ms_ads_list, nsecs)
            VLCAccOOIData_AccOOINextLong_Attributes_uiObjectID=list_data[2]
            EnvmGenObjectList_aObject_0_Kinematic_fDistX=list_data[5]
            EnvmGenObjectList_aObject_0_Kinematic_fVabsX=list_data[7]
            EnvmGenObjectList_aObject_1_Kinematic_fDistX = list_data[11]
            EnvmGenObjectList_aObject_1_Kinematic_fVabsX = list_data[13]
            EnvmGenObjectList_aObject_2_Kinematic_fDistX = list_data[17]
            EnvmGenObjectList_aObject_2_Kinematic_fVabsX = list_data[19]
            EnvmGenObjectList_aObject_3_Kinematic_fDistX = list_data[23]
            EnvmGenObjectList_aObject_3_Kinematic_fVabsX = list_data[25]
            EnvmGenObjectList_aObject_4_Kinematic_fDistX = list_data[29]
            EnvmGenObjectList_aObject_4_Kinematic_fVabsX = list_data[31]
            EnvmGenObjectList_aObject_5_Kinematic_fDistX = list_data[35]
            EnvmGenObjectList_aObject_5_Kinematic_fVabsX = list_data[37]
            if  VLCAccOOIData_AccOOINextLong_Attributes_uiObjectID==0:
                ttc = EnvmGenObjectList_aObject_0_Kinematic_fDistX /(EnvmGenObjectList_aObject_0_Kinematic_fVabsX-IDB3_VehicleSpd / 3.6)
                IDB3_VehicleSpd_flag=IDB3_VehicleSpd / 3.6
                if (IDB3_VehicleSpd_flag<=1 and ttc<0.8) or (IDB3_VehicleSpd_flag<=3 and (ttc<0.25*IDB3_VehicleSpd_flag+0.55)) or \
                   (IDB3_VehicleSpd_flag>3 and IDB3_VehicleSpd_flag<=10 and (ttc<0.1*IDB3_VehicleSpd_flag+1)) or \
                   (IDB3_VehicleSpd_flag>10 and ttc<2):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "ttc"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)

                gap = EnvmGenObjectList_aObject_0_Kinematic_fDistX / (IDB3_VehicleSpd / 3.6)
                if (IDB3_VehicleSpd_flag<=1 and gap<1) or (IDB3_VehicleSpd_flag<=10 and gap<-0.092857143*IDB3_VehicleSpd_flag+1.278571429) or \
                   (IDB3_VehicleSpd_flag>10 and IDB3_VehicleSpd_flag<=30 and gap<-0.0085*IDB3_VehicleSpd_flag+0.435):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "time gap"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)

            elif  VLCAccOOIData_AccOOINextLong_Attributes_uiObjectID==1:
                ttc = EnvmGenObjectList_aObject_1_Kinematic_fDistX /(EnvmGenObjectList_aObject_1_Kinematic_fVabsX-IDB3_VehicleSpd / 3.6)
                IDB3_VehicleSpd_flag = IDB3_VehicleSpd / 3.6
                if (IDB3_VehicleSpd_flag <= 1 and ttc < 0.8) or (
                        IDB3_VehicleSpd_flag <= 3 and (ttc < 0.25 * IDB3_VehicleSpd_flag + 0.55)) or \
                        (IDB3_VehicleSpd_flag > 3 and IDB3_VehicleSpd_flag <= 10 and (ttc < 0.1 * IDB3_VehicleSpd_flag + 1)) or \
                        (IDB3_VehicleSpd_flag > 10 and ttc < 2):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "ttc"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)

                gap = EnvmGenObjectList_aObject_1_Kinematic_fDistX / (IDB3_VehicleSpd / 3.6)
                if (IDB3_VehicleSpd_flag<=1 and gap<1) or (IDB3_VehicleSpd_flag<=10 and gap<-0.092857143*IDB3_VehicleSpd_flag+1.278571429) or \
                   (IDB3_VehicleSpd_flag>10 and IDB3_VehicleSpd_flag<=30 and gap<-0.0085*IDB3_VehicleSpd_flag+0.435):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "time gap"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)

            elif  VLCAccOOIData_AccOOINextLong_Attributes_uiObjectID==2:
                ttc = EnvmGenObjectList_aObject_2_Kinematic_fDistX /(EnvmGenObjectList_aObject_2_Kinematic_fVabsX-IDB3_VehicleSpd / 3.6)
                IDB3_VehicleSpd_flag = IDB3_VehicleSpd / 3.6
                if (IDB3_VehicleSpd_flag <= 1 and ttc < 0.8) or (IDB3_VehicleSpd_flag <= 3 and (ttc < 0.25 * IDB3_VehicleSpd_flag + 0.55)) or \
                    (IDB3_VehicleSpd_flag > 3 and IDB3_VehicleSpd_flag <= 10 and (ttc < 0.1 * IDB3_VehicleSpd_flag + 1)) or \
                    (IDB3_VehicleSpd_flag > 10 and ttc < 2):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "ttc"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)

                gap = EnvmGenObjectList_aObject_2_Kinematic_fDistX / (IDB3_VehicleSpd / 3.6)
                if (IDB3_VehicleSpd_flag<=1 and gap<1) or (IDB3_VehicleSpd_flag<=10 and gap<-0.092857143*IDB3_VehicleSpd_flag+1.278571429) or \
                   (IDB3_VehicleSpd_flag>10 and IDB3_VehicleSpd_flag<=30 and gap<-0.0085*IDB3_VehicleSpd_flag+0.435):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "time gap"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)
            elif  VLCAccOOIData_AccOOINextLong_Attributes_uiObjectID==3:
                ttc = EnvmGenObjectList_aObject_3_Kinematic_fDistX /(EnvmGenObjectList_aObject_3_Kinematic_fVabsX-IDB3_VehicleSpd / 3.6)
                IDB3_VehicleSpd_flag = IDB3_VehicleSpd / 3.6
                if (IDB3_VehicleSpd_flag <= 1 and ttc < 0.8) or (IDB3_VehicleSpd_flag <= 3 and (ttc < 0.25 * IDB3_VehicleSpd_flag + 0.55)) or \
                   (IDB3_VehicleSpd_flag > 3 and IDB3_VehicleSpd_flag <= 10 and (ttc < 0.1 * IDB3_VehicleSpd_flag + 1)) or \
                   (IDB3_VehicleSpd_flag > 10 and ttc < 2):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "ttc"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)

                gap = EnvmGenObjectList_aObject_3_Kinematic_fDistX / (IDB3_VehicleSpd / 3.6)
                if (IDB3_VehicleSpd_flag<=1 and gap<1) or (IDB3_VehicleSpd_flag<=10 and gap<-0.092857143*IDB3_VehicleSpd_flag+1.278571429) or \
                   (IDB3_VehicleSpd_flag>10 and IDB3_VehicleSpd_flag<=30 and gap<-0.0085*IDB3_VehicleSpd_flag+0.435):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "time gap"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)
            elif  VLCAccOOIData_AccOOINextLong_Attributes_uiObjectID==4:
                ttc = EnvmGenObjectList_aObject_4_Kinematic_fDistX / (EnvmGenObjectList_aObject_4_Kinematic_fVabsX - IDB3_VehicleSpd / 3.6)
                IDB3_VehicleSpd_flag = IDB3_VehicleSpd / 3.6
                if (IDB3_VehicleSpd_flag <= 1 and ttc < 0.8) or (IDB3_VehicleSpd_flag <= 3 and (ttc < 0.25 * IDB3_VehicleSpd_flag + 0.55)) or \
                   (IDB3_VehicleSpd_flag > 3 and IDB3_VehicleSpd_flag <= 10 and (ttc < 0.1 * IDB3_VehicleSpd_flag + 1)) or \
                   (IDB3_VehicleSpd_flag > 10 and ttc < 2):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "ttc"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)

                gap = EnvmGenObjectList_aObject_4_Kinematic_fDistX / (IDB3_VehicleSpd / 3.6)
                if (IDB3_VehicleSpd_flag<=1 and gap<1) or (IDB3_VehicleSpd_flag<=10 and gap<-0.092857143*IDB3_VehicleSpd_flag+1.278571429) or \
                   (IDB3_VehicleSpd_flag>10 and IDB3_VehicleSpd_flag<=30 and gap<-0.0085*IDB3_VehicleSpd_flag+0.435):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "time gap"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)
            elif  VLCAccOOIData_AccOOINextLong_Attributes_uiObjectID==5:
                ttc = EnvmGenObjectList_aObject_5_Kinematic_fDistX / (EnvmGenObjectList_aObject_5_Kinematic_fVabsX - IDB3_VehicleSpd / 3.6)
                IDB3_VehicleSpd_flag = IDB3_VehicleSpd / 3.6
                if (IDB3_VehicleSpd_flag <= 1 and ttc < 0.8) or (IDB3_VehicleSpd_flag <= 3 and (ttc < 0.25 * IDB3_VehicleSpd_flag + 0.55)) or \
                   (IDB3_VehicleSpd_flag > 3 and IDB3_VehicleSpd_flag <= 10 and (ttc < 0.1 * IDB3_VehicleSpd_flag + 1)) or \
                   (IDB3_VehicleSpd_flag > 10 and ttc < 2):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "ttc"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)

                gap = EnvmGenObjectList_aObject_5_Kinematic_fDistX / (IDB3_VehicleSpd / 3.6)
                if (IDB3_VehicleSpd_flag<=1 and gap<1) or (IDB3_VehicleSpd_flag<=10 and gap<-0.092857143*IDB3_VehicleSpd_flag+1.278571429) or \
                   (IDB3_VehicleSpd_flag>10 and IDB3_VehicleSpd_flag<=30 and gap<-0.0085*IDB3_VehicleSpd_flag+0.435):
                    dict = {}
                    dict["vehicle_id"] = vechicle_id
                    dict["start_time_str"] = start_time_str
                    dict["scid"] = bagid
                    dict["path"] = path
                    level1 = "ADAS预期接管"
                    level2 = "纵向接管请求"
                    level3 = "time gap"
                    dict["level1"] = level1
                    dict["level2"] = level2
                    dict["level3"] = level3
                    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                    month = start_time_str[0:4] + start_time_str[5:7]
                    dict["day"] = day
                    dict["month"] = month
                    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                    print("start_time_str_100: " + start_time_str)
                    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                    dict["uid"] = uid

                    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                    print("start_time_str_100: " + start_time_str)
                    timestamp = get_timestamp(start_time_str)
                    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                    label_bucket_name = "bigdatatest"
                    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                    uploadjson(label_bucket_name, labe_object_key, json_string)
            if (AccDisplayObj_CONTROL_ACCEL<-4.6 and IDB3_VehicleSpd/3.6<=5) or \
                ((IDB3_VehicleSpd/3.6>5 and IDB3_VehicleSpd/3.6<=20) and AccDisplayObj_CONTROL_ACCEL<0.066666667*(IDB3_VehicleSpd/3.6)-4.933333333) or \
                (IDB3_VehicleSpd/3.6>20 and AccDisplayObj_CONTROL_ACCEL< -3.6):
                dict = {}
                dict["vehicle_id"] = vechicle_id
                dict["start_time_str"] = start_time_str
                dict["scid"] = bagid
                dict["path"] = path
                level1 = "ADAS预期接管"
                level2 = "纵向接管请求"
                level3 = "a requset"
                dict["level1"] = level1
                dict["level2"] = level2
                dict["level3"] = level3
                day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
                month = start_time_str[0:4] + start_time_str[5:7]
                dict["day"] = day
                dict["month"] = month
                dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
                dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
                dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
                dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
                dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
                dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
                dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
                dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
                dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]

                print("start_time_str_100: " + start_time_str)
                uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
                uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
                dict["uid"] = uid

                json_string = json.dumps(dict, ensure_ascii=False, indent=None)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)

                print("start_time_str_100: " + start_time_str)
                timestamp = get_timestamp(start_time_str)
                input_string = vechicle_id + bagid + timestamp + uuids + file_type + level2 + level3
                filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
                label_bucket_name = "bigdatatest"
                labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
                uploadjson(label_bucket_name, labe_object_key, json_string)




        print("记录上一条数据")
        ADCS8_lateralCtrtakeove_last=ADCS8_lateralCtrtakeove
        ADCS8_longitudCtrlTakeOverReq_last=ADCS8_longitudCtrlTakeOverReq
    add_to_bytehouse(dict_list)
def get_model_expected_takeover_ads_can_100ms(df_can_100ms_save_path, vechicle_id, daystr, hourstr, bagid, uuids, file_type, dtc,sc):
    try:
        df_expected_takeover_ads_100ms = pd.read_pickle(df_can_100ms_save_path)
        print(df_expected_takeover_ads_100ms.columns)
    except Exception as e:
        print('data report read error, ', str(e))
    df_expected_takeover_ads_100ms_list = df_expected_takeover_ads_100ms[
        ['start_time_str', 'path', 'nsecs', 'VLCCDHypotheses_Hypothesis_0_fTTC', 'VLCCDHypotheses_Hypothesis_0_fDistX',
         'VLCCDHypotheses_Hypothesis_0_fDistY',
         'VLCCDHypotheses_Hypothesis_0_fVrelX', 'VLCCDHypotheses_Hypothesis_0_fVrelY', 'IDB3_VehicleSpd',
         'ACU2_LongAccSensorValue', 'ACU2_LatAccSensorValue',
         'ACU2_VehicleDynYawRate', 'IDB1_BrakePedalApplied', 'EPS1_SteerAngleSpd',
         'CamLaneData_CourseInfo_1_CourseInfoSegNear_f_C0',
         'ADCS8_longitudCtrlTakeOverReq', 'ADCS8_lateralCtrtakeove','ICU2_Odometer','EPS1_TorsionBarTorque','CS1_GearPositionReqSt'
         ]].values.tolist()


    found_index = -9999
    start_time_str = ""
    found_ICU2_Odometer=0.0
    found_IDB3_VehicleSpd=0.0
    found_ACU2_LongAccSensorValue=0.0
    found_ACU2_LatAccSensorValue=0.0
    found_ACU2_VehicleDynYawRate=0.0
    found_EPS1_SteerAngleSpd=0.0
    found_EPS1_TorsionBarTorque=0.0
    found_CS1_GearPositionReqSt=0
    # 遍历列表

    for index, element in enumerate(df_expected_takeover_ads_100ms_list):
        start_time_str = element[0]
        path = element[1]
        nsecs = element[2]
        ADCS8_longitudCtrlTakeOverReq = element[15]
        ADCS8_lateralCtrtakeove = element[16]

        ICU2_Odometer = element[17]
        IDB3_VehicleSpd = element[8]
        ACU2_LongAccSensorValue = element[9]
        ACU2_LatAccSensorValue = element[10]
        ACU2_VehicleDynYawRate = element[11]
        EPS1_SteerAngleSpd = element[13]
        EPS1_TorsionBarTorque = element[18]
        CS1_GearPositionReqSt = element[19]
        if (ADCS8_longitudCtrlTakeOverReq==1) or (ADCS8_lateralCtrtakeove==1):
            found_index = index
            found_ICU2_Odometer = ICU2_Odometer
            found_IDB3_VehicleSpd = IDB3_VehicleSpd
            found_ACU2_LongAccSensorValue = ACU2_LongAccSensorValue
            found_ACU2_LatAccSensorValue = ACU2_LatAccSensorValue
            found_ACU2_VehicleDynYawRate = ACU2_VehicleDynYawRate
            found_EPS1_SteerAngleSpd = EPS1_SteerAngleSpd
            found_EPS1_TorsionBarTorque = EPS1_TorsionBarTorque
            found_CS1_GearPositionReqSt = CS1_GearPositionReqSt

            break  # 找到第一个符合条件的元素就跳出循环
    logging.info("found_index: " + str(found_index))
    df=get_model_feature(found_index, df_expected_takeover_ads_100ms_list, start_time_str)
    df_std = sc.transform(df)
    y_pred = dtc.predict(df_std)
    logging.info("预测结果： " + str(y_pred))
    # 输出值为2代表已碰撞，1代表危险但未碰撞，0代表不危险
    if y_pred[0] == 2:
        level1 = "已碰撞"
    elif y_pred[0] == 1:
        level1 = "危险但未碰撞"
    elif y_pred[0] == 0:
        level1 = "不危险"
    dict = {}
    dict["vehicle_id"] = vechicle_id
    dict["start_time_str"] = start_time_str
    dict["scid"] = bagid
    dict["path"] = path
    level2 = ""
    level3 = ""
    dict["level1"] = level1
    dict["level2"] = level2
    dict["level3"] = level3
    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
    month = start_time_str[0:4] + start_time_str[5:7]
    dict["day"] = day
    dict["month"] = month
    dict["scid_start_time_str"] = start_time_str
    dict["icu2_odometer"] = ICU2_Odometer
    dict["idb3_vehiclespd"] = IDB3_VehicleSpd
    dict["acu2_longaccsensorvalue"] = ACU2_LongAccSensorValue
    dict["acu2_lataccsensorvalue"] = ACU2_LatAccSensorValue
    dict["acu2_vehicledynyawrate"] = ACU2_VehicleDynYawRate
    dict["eps1_steeranglespd"] = EPS1_SteerAngleSpd
    dict["eps1_torsionbartorque"] = EPS1_TorsionBarTorque
    dict["cs1_gearpositionreqst"] = CS1_GearPositionReqSt

    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
    dict["uid"] = uid

    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
    add_to_bytehouse_dict(dict)

    timestamp = get_timestamp(start_time_str)
    input_string = vechicle_id + bagid + timestamp + uuids + file_type + level3
    filename = str(uuid.uuid3(uuid.NAMESPACE_DNS, input_string)) + ".json"
    label_bucket_name = "bigdatatest"
    labe_object_key = "EP40/TDA4/LABEL/" + daystr + "/" + hourstr + "/" + vechicle_id + "/" + filename
    uploadjson(label_bucket_name, labe_object_key, json_string)
